Abstract

Analysts play very important roles in financial markets. They add value to the market in general and the investors in particular by providing highly useful and well-researched information. However, it is noted that a number of researchers in the past have concluded that the forecasts made by the analysts are not efficient as there are a number of biases that have been found to be involved in these forecasts. This research attempts to test the efficiency of the analysts’ forecasts. In turn, this research attempts to ascertain the validity of the rational expectations hypothesis, which states that the analysts forecast the economic outcomes of different variables accurately. This research attempts to accomplish its objective through the use of empirical analysis of the data drawn from the forecasts made by the analysts about the earnings of the UK companies for a period between 1986 and 2003. This research tests the efficiency using two different assumptions – quadratic loss function and linear loss function. Therefore two different estimation methods are used for linear regression – Ordinary Least Squares (OLS) and Least Absolute Deviation (LAD). The results of the application of these estimation methods show that these two methods tend to lead to contradictory observations. While the OLS leads to a conclusion that the forecasts are inefficient, the LAD shows that there is nothing significant in the results to doubt the efficiency of the forecasts of analysts. However it is noted that LAD may be a more suitable method as the analysts are generally concerned about the absolute deviations and not the squared

deviations and the earnings and forecasts are not normally distributed. On this basis it is concluded that the forecasts of analysts are efficient in nature. It is also concluded that the rational expectations hypothesis cannot be rejected on the basis of the results obtained.